Ultra-High Resolution Information Visualization

1. Ultra-High Resolution Information Visualization CS 5764 Sarah Peck, Chris North Credits: Beth Yost, Bob Ball, Christopher Andrews, Mike DellaNoce, Candice Luebbering, Sarah Peck, Lauren Shupp, John Booker

2. Research Questions What is the impact of large high-resolution displays on visualization? • Fundamental issues: • What is the benefit for visualization?in terms of Perception, Navigation, Awareness • Limits of visual scalability? • Display design issues: • How big? How shaped? • Visualization design issues: • How to embed more information? • Interaction design issues: • How to point? pan? zoom?

3. Empirical Results: High-Resolution Analytic force multiplier • 2-10x faster task performance • Curved displays speed some tasks by 30% • Reduce frustration by 50% • Reduce virtual navigation actions by 75% • Increase physical navigation 300% • Analyze 22x more data, only 3x more time, while maintaining accuracy • Greater situational awareness • Easier interaction • Short initial learning time

4. Display Space constant density line Pixel Density = # of pixels / display size “Resolution” = density? or # of pixels? Physical Size of display # of pixels

5. VT GigaPixel Laboratory • ~200 Mpixels, scalable • Reconfigurable • Multiple display technologies • Diverse input devices • Link to AwareLab, VICON

6. Analyst Workspace Options 9 tiled LCD panels Single CPU MS Windows Small cubicle < $5,000 24 tiled LCD panels Curved configuration Multi-CPU Large cubicle/office ~ $20,000

7. Collaborative Workspace Options 18 Rear-projection blocks near-seamless Multi-CPU Large conference room ~ $150,000 50 tiled LCD panels Touch-sensitive Multi-CPU Medium conference room ~ $120,000

8. LCD vs. Rear-projection

9. Variables • # pixels, display size, density • Shape, curvature, horizontal / vertical • Brightness, contrast, color, clarity • Uniformity • Alignment • Bezels, seams • Technology type • Footprint • Maintenance • Input technique

10. User Input Devices / Techniques Videos…

11. High-Res Visualization Design

12. Displaying more data • More entities • More attributes • Embed details • Larger spatial area • Multiple levels of scale • Heterogeneous data • Task context info

13. More entities

14. More attributes

15. Embed details • Storyboard notecards

16. Design Suggestions • Take advantage of fast physical navigation to replace slow virtual navigation • Design to take advantage of visual aggregation • Consider what is perceptible from various physical distances • Consider multiple strategic labels and both local and global legends • Choose scalable encodings • Consider effect of display characteristics

17. Enable Physical Navigation • To reduce Virtual Navigation (mouse…) • Avoid tethered input devices

18. Visual Aggregation Like semantic zooming

19. Physical Adaptation

20. Physical Adaptation

21. Strategic Placement • Consider multiple strategic labels and both local and global legends

22. Graphically Scalable Encodings

23. Today’s paper • Shupp et al “Size and curvature of Hi-Res displays” • Presenter: Sunghee Park

24. Empirical Results

25. More pixels = Faster Vis Task Performance Display size vs. User’s task performance time Users were 8 times faster with 8 times more screen space  Faster Larger display size →

26. Physical Navigation • Wide field of view

27. Greater Situational Awareness With more pixels: • 92% claim greater awareness • 70% claim easier interaction • Subjects used more proactive strategies With larger screens, users were more aware due to spending less percentage of their time navigating.

28. 1 Monitor 1% 2% 4 Monitors 35% 45% <1% 4% 9% 1% 16% 2% 8% <1% 4% 2% <1% 6% 64% More Time on Task With larger display, analysts spent more time on task and less time on interface manipulation

29. Less Time Wasted Average # of Mouse Clicks by Display Size With larger screen, ¼ fewer mouse clicks to accomplish the same analytic tasks Mouse Clicks # of Monitor(s)

30. Curvature • Faster task performance than flat, 30% • Causes different insight than flat • Localized vs global insights

31. Data Scalability: Beyond Visual Acuity

32. Small Multiples 32 Mp 2 Mp Demographic Groups Years US Map White Female 1976

33. Embedded Visualizations US Map Demographic Groups Bar Matrix Years Time-Series Graph

34. Data Scalability: Beyond Visual Acuity • Efficient: 17x more data, 2x more time • Accuracy maintained • Embedded vis design scales better • Spatial grouping is important on Large Displays • Used physical navigation & visual aggregation

35. Publications • CHI 2005: “Effects of Tiled, High-Resolution …” • Interact 2005: “Analysis of User Behavior…” • HCI 2005: “Evaluating the Benefits…for Navigating Maps” • AAG 2006: “Map Reading Efficiency on High-Resolution…” • Graphics Interface 2006: “Viewport Size & Curvature…” • ISI 2006: “Intelligence Analysis using High-Resolution…” • InfoVis 2006: “Scalability of Visualization…” and Demo • Interacting with Computers: “High-Resolution Gaming…” • British HCI: “Applying Embodied Interaction…” • Computers & Graphics: “Realizing Embodied Interaction…” • IVS: “Designing Info Visualizations for Hi-Res…” • CHI 2007: “Perceptual Scalability with Hi-Res…” • CHI 2007: “Physical vs Virtual Navigation…”